EP4050365A1 - Verfahren und system zur zeitmultiplex mimo radardoppler-kompensation unter verwendung von hypothesentests mit störwinkelspektrum - Google Patents

Verfahren und system zur zeitmultiplex mimo radardoppler-kompensation unter verwendung von hypothesentests mit störwinkelspektrum Download PDF

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EP4050365A1
EP4050365A1 EP22157351.2A EP22157351A EP4050365A1 EP 4050365 A1 EP4050365 A1 EP 4050365A1 EP 22157351 A EP22157351 A EP 22157351A EP 4050365 A1 EP4050365 A1 EP 4050365A1
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Prior art keywords
hypothesis
doppler
radar
threshold
phase
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French (fr)
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Ryan Haoyun Wu
Dongying Ren
Satish Ravindran
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NXP USA Inc
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NXP USA Inc
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/03—Details of HF subsystems specially adapted therefor, e.g. common to transmitter and receiver
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/50—Systems of measurement based on relative movement of target
    • G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G01S13/581—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of interrupted pulse modulated waves and based upon the Doppler effect resulting from movement of targets
    • G01S13/582—Velocity or trajectory determination systems; Sense-of-movement determination systems using transmission of interrupted pulse modulated waves and based upon the Doppler effect resulting from movement of targets adapted for simultaneous range and velocity measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/10—Systems for measuring distance only using transmission of interrupted, pulse modulated waves
    • G01S13/26—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave
    • G01S13/28—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses
    • G01S13/282—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses using a frequency modulated carrier wave
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/288—Coherent receivers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers
    • G01S7/292—Extracting wanted echo-signals

Definitions

  • This disclosure relates generally to radar systems and associated methods of operation, and more specifically, to resolving Doppler ambiguity and multiple-input, multiple-output (MIMO) phase compensation issues present in time-division multiplexing MIMO radars.
  • MIMO multiple-input, multiple-output
  • Radar systems are used to detect the range, velocity, and angle of targets. With advances in technology, radar systems can now be applied in many different applications, such as automotive radar safety systems, but not every radar system is suitable for every application.
  • FMCW Frequency Modulation Continuous Wave
  • FCM Fast Chirp Modulation
  • MIMO multiple-input, multiple-output arrays as sensors in Advanced Driver Assistance System (ADAS) and autonomous driving (AD) systems.
  • ADAS Advanced Driver Assistance System
  • AD autonomous driving
  • a Time Division Multiplexed (TDM) linear-chirp waveform is the most common waveform used in mm-Wave FMCW automotive radar systems for constructing a MIMO virtual aperture to achieve higher angular resolution.
  • the TDM approach simplifies MIMO transmission as well as receiving processing, which leads to lower cost and more effective implementations.
  • Time multiplexing of chirps transmitted by different transmitter antennas can result in mismatched phase delays caused by motion of targets. This mismatched phase delay needs to be compensated for with additional processing. But to perform such compensation, radar signal processing needs to estimate unambiguous radial velocity measurements.
  • Embodiments of the present invention resolve Doppler ambiguity and multiple-input, multiple-output array phase compensation issues present in Time Division Multiplexing MIMO radars by estimating an unambiguous radial velocity measurement.
  • Embodiments apply a disambiguation algorithm that dealiases the Doppler spectrum to resolve the Doppler ambiguity of a range-Doppler detection.
  • Phase compensation is then applied for corrected reconstruction of the MIMO array measurements.
  • the dealiasing processing first forms multiple hypotheses associated with the phase corrections for the radar transmitters based on a measured radial velocity of a range-Doppler cell being processed.
  • a correct hypothesis, from the multiple hypotheses, is selected based on a least-spurious spectrum criterion. Using this approach, embodiments require only single-frame processing and can be applied to two or more transmitters in a TDM MIMO radar system.
  • radar systems may be used as sensors in a variety of different applications, including but not limited to automotive radar sensors for road safety systems, such as advanced driver-assistance systems (ADAS) and autonomous driving (AD) systems.
  • ADAS advanced driver-assistance systems
  • AD autonomous driving
  • the radar systems are used to measure radial distance to a reflecting object, its relative radial velocity, and angle information, and are characterized by performance criteria, such as the angular resolution (e.g., a minimum distance between two equally large targets at the same range and range rate, or radial velocity, cell at which a radar is able to distinguish and separate the targets), sensitivity, false detection rate, and the like.
  • the angular resolution e.g., a minimum distance between two equally large targets at the same range and range rate, or radial velocity, cell at which a radar is able to distinguish and separate the targets
  • sensitivity false detection rate
  • FMCW modulated continuous wave (FMCW) modulation radars are used to identify the distance, velocity, and/or angle of a radar target, such as a car or pedestrian, by transmitting Linear Frequency Modulation (LFM) waveforms from multiple transmit antennas so that reflected signals from the radar target are received at multiple receive antennas and processed to determine the radial distance, relative radial velocity, and angle (or direction) for the radar target.
  • LFM Linear Frequency Modulation
  • a vehicle can include multiple radar transmitters that operate independently from one another.
  • the LFM waveform transceivers may be configured to implement time-division (TD) MIMO operations to temporally separate signals originated from distinct transmitters so that a receiving channel can distinctly detect each signal and thereby construct a virtual MIMO array.
  • TD time-division
  • FIG. 1 depicts a simplified schematic block diagram of a conventional LFM TD-MIMO automotive radar system 100 which includes an LFM TD-MIMO radar device 110 connected to a radar microcontroller and processing unit (“radar MCPU") 150.
  • the LFM TD-MIMO radar device 110 may be embodied as a line-replaceable unit (LRU) or modular component that is designed to be replaced quickly at an operating location.
  • the radar microcontroller and processing unit 150 may be embodied as a line-replaceable unit (LRU) or modular component.
  • LFM TD-MIMO radar device 110 Although a single or mono-static LFM TD-MIMO radar device 110 is shown, it will be appreciated that additional distributed radar devices may be used to form a distributed or multi-static radar.
  • the depicted radar system 100 may be implemented in integrated circuit form with the LFM TD-MIMO radar device 10 and the radar microcontroller and processing unit 150 formed with separate integrated circuits (chips) or with a single chip, depending on the application.
  • Each radar device 110 includes one or more transmitting antenna elements TX i and receiving antenna elements RX j connected, respectively, to one or more radio-frequency (RF) transmitter (TX) units 120 and receiver (RX) units 140.
  • each radar device e.g., 110
  • each radar device is shown as including individual antenna elements (e.g., TX 1,i , RX 1,j ) connected, respectively, to three transmitter modules (e.g., 120) and four receiver modules (e.g., 140), but these numbers are not limiting, and other numbers are also possible, such as four transmitter modules 120 and six receiver modules 140, or a single transmitter module 120 and/or a single receiver module 140.
  • Each radar device 110 also includes a chirp generator 135 which is configured and connected to supply a chirp input signal to the transmitter modules 120.
  • the chirp generator 135 is connected to receive a separate and independent local oscillator (LO) signal and a chirp start trigger signal (illustrated as 130), though delays are likely to be different due to the signal path differences and programmable digital delay elements in the signal paths.
  • Chirp signals 137 are generated and transmitted to multiple transmitters 120, usually following a pre-defined transmission schedule, where they are filtered at the RF conditioning module 122 and amplified at the power amplifier 124 before being fed to the corresponding transmit antenna TX 1,i and radiated.
  • each transmitter element 120 By sequentially using each transmit antenna TX 1,i to transmit successive pulses in the chirp signal 137, each transmitter element 120 operates in a time-multiplexed fashion in relation to other transmitter elements because they are programmed to transmit identical waveforms on a temporally separated schedule.
  • the radar signal transmitted by the transmitter antenna unit TX 1,i , TX 2,i may be reflected by an object, and part of the reflected radar signal reaches the receiver antenna units RX 1,i at the radar device 110.
  • the received (radio frequency) antenna signal is amplified by a low noise amplifier (LNA) 141 and then fed to a mixer 142 where it is mixed with the transmitted chirp signal generated by the RF conditioning unit 122.
  • the resulting intermediate frequency signal is fed to a first high-pass filter (HPF) 144.
  • HPF high-pass filter
  • the resulting filtered signal is fed to a first variable gain amplifier 146 which amplifies the signal before feeding it to a first low pass filter (LPF) 148.
  • LPF low pass filter
  • This re-filtered signal is fed to an analog/digital converter (ADC) 149 and is output by each receiver module 140 as a digital signal D1.
  • ADC analog/digital converter
  • the receiver module compresses target echo of various delays into multiple sinusoidal tones whose frequencies correspond to the round-trip delay of the echo.
  • the radar system 100 also includes a radar microcontroller and processing unit 150 that is connected to supply input control signals to the radar device 110 and to receive therefrom digital output signals generated by the receiver modules 140.
  • the radar microcontroller and processing unit 150 may be embodied as a micro-controller unit (MCU) or other processing unit that is configured and arranged for signal processing tasks such as, but not limited to, target identification, computation of target distance, target velocity, and target direction, and generating control signals.
  • Radar controller 155 can, for example, be configured to generate calibration signals, receive data signals, receive sensor signals, generate frequency spectrum shaping signals (such as ramp generation in the case of FMCW radar) and/or register programming or state machine signals for RF (radio frequency) circuit enablement sequences.
  • the radar controller processor 155 may be configured to program the modules 120 to operate in a time-division fashion by sequentially transmitting LFM chirps for coordinated communication between the transmit antennas TX 1,i , RX 1,j .
  • the result of the digital processing at the radar microcontroller and processing unit 150 is that the digital domain signals D1 are processed for the subsequent fast-time range fast-Fourier transform (FFT) (160), which generates a range chirp antenna cube matrix 162.
  • FFT fast-time range fast-Fourier transform
  • Range chirp antenna cube 162 is provided to a slow-time Doppler FFT processing (165) to generate a range Doppler antenna cube matrix 167.
  • the range Doppler antenna cube is provided to a constant false alarm rate (CFAR) target detection processing (170) that generates a set of detected range-Doppler cells 172.
  • TD MIMO Array Construction processing (175) generates an uncompensated array vector 177, which contains errors in phase delays from moving targets.
  • Doppler disambiguation and phase compensation (180) is then performed to provide a phase compensated array vector 182.
  • Spatial angle estimation (185) and target tracking processing (190) can then be performed, generated target plots 187 and target tracks 192, respectively.
  • the result is then output to other automotive computing or user interfacing devices (195) for further process or display.
  • FIG. 2 is a simplified block diagram depicting an example of a chirp transmission schedule 200 of a 3-TX TDM MIMO radar system.
  • Three transmission antennae TX i TX 1 , TX 2 , and TX 3 (210), are sequentially alternated to transmit radar chirps (Chirp 1 - Chirp N).
  • a chirp interval time (CIT) separates the beginning of each successive chirp, while a pulse repetition interval (PRI) designates the time for a cycle of all the transmitters.
  • the reflections of the transmitted chirps from targets within the range of the radar are received by a set of receivers RX j : RX 1 , RX 2 , RX 3 , RX 4 (220).
  • Range-Doppler response maps of the four illustrated receivers from the three illustrated transmission CIT periods are aggregated to form a MIMO array measurement data cube (e.g., range chirp antenna cube 162) consisting of range-Doppler response maps of 12 antenna elements of a constructed MIMO virtual array (230).
  • a MIMO array measurement data cube e.g., range chirp antenna cube 162
  • range-Doppler responses are then non-coherently integrated and target detection is attempted on the energy-combined range-Doppler map.
  • a detection algorithm such as any variant of the CFAR algorithm (e.g., 170), is commonly used to identify those range-Doppler cells in which targets may be present (e.g., detected range-Doppler cells 172).
  • an array measurement vector is extracted (e.g., uncompensated array vector 177) and processed to determine the incident angles of the target returns contained in the cell.
  • This process is complicated by the TDM MIMO operation in which MIMO transmitters are transmitting at different times. Further, there can be relative motion between the radar and the targets.
  • FIG. 3 is a simplified block diagram illustrating an interaction between the radar and a moving target within 2 consecutive PRIs: PRI#1 and PRI#2.
  • Each PRI consists of three chirp transmission periods corresponding to each of three transmitters (e.g., t 1 , t 2 , and t 3 for PRI#1 and t 4 , t 5 , and t 6 for PRI#2).
  • This change in distance translates to a change in the round-trip phase delay of the reflected return signals.
  • the round-trip phase delay causes phase offsets across subsequent transmission periods.
  • phase offsets must be compensated for to generate the equivalent of simultaneous transmission and perfect separation of transmitter signals of an "ideal" MIMO radar system in which distance-change induced phase offsets do not exist. This is performed during Doppler disambiguation and phase compensation processing 180 of Figure 1 .
  • the MIMO virtual array antennas 230 can be designated as a two-dimensional matrix VR i,j .
  • An element x i,j is the output of RX j when TX i is transmitting.
  • phase offsets can be compensated when the radial velocity of the target and the time between the transmissions are known. Assuming each detection cell has only one target present, an estimated radial velocity of the target is readily available from the cell's corresponding Doppler frequency. Phase offset is then calculated based on the twice the distance travelled by the target between the two transmission events.
  • Figures 4 and 5 are angle spectrum charts illustrating examples of erroneous angle spectrums from uncompensated TDM MIMO array measurement vectors. If the data is left uncompensated, then the estimated target angles would likely be corrupted.
  • Figure 4 illustrates an example of a 12-element MIMO virtual array measurement vector with one target present in a range-Doppler cell. Due to target motion and incorrectly compensated phase error (or not compensated for phase error), a phase discontinuity is present in the MIMO array measurement vector 422 in plot 420 and the resulting angle spectrum is distorted (curve 412 on plot 410). Curves 415 and 425 indicate the cases of correctly compensated measurement vector in plot 420 and angle spectrum in plot 410. The incorrectly compensated angle spectrum 412 results in two incorrect peaks 413 and 414, while the correctly compensated spectrum has a peak 416 corresponding to the correct spatial frequency.
  • Figure 5 illustrates an example of a 12-element MIMO virtual array measurement vector with two targets present in a range-Doppler cell. Due to target motion and incorrectly compensated phase error (or not compensated for phase error), a phase discontinuity is present in the MIMO array measurement vector 522 in plot 520 and the resulting angle spectrum is distorted (curve 512 on plot 510). Curves 517 and 525 indicate the cases of correctly compensated measurement vector in plot 520 and angle spectrum in plot 510. The incorrectly compensated angle spectrum 512 results in a set of incorrect peaks 513-516, while the correctly compensated spectrum has peaks 518 and 519 corresponding to the correct spatial frequency.
  • the correctly compensated angle spectrums may or may not have higher peak response than the uncompensated spectrums (e.g., curves 412 and 512).
  • a strongest-peak criterion cannot be reliably used as an indicator for absence of phase discontinuity in a constructed MIMO array measurement vector.
  • a different solution that correctly estimates radial velocity in the presence of Doppler ambiguity is needed.
  • Embodiments provide a disambiguation algorithm to de-alias Doppler spectrum and resolve Doppler ambiguity of a range-Doppler detection. Phase compensation is then applied to correctly reconstruct MIMO array measurements. Dealiasing first forms multiple hypotheses regarding phase corrections for the transmitters based on the measured radial velocity of a detected range-Doppler cell being processed. Selection of the correct hypothesis is performed based on a least-spurious spectrum criterion, as will be illustrated below. This approach is scalable to two or more transmitters in a TDM MIMO radar system, unlike certain prior art systems.
  • FIG 11 is a simplified flow diagram illustrating an example of a process used to determine a phase compensation associated with a TDM MIMO array element in accordance with an embodiment of the present invention. This process can be executed as part of Doppler disambiguation and phase compensation processing (180) executed by the receiver processor of Radar MCPU 150.
  • a first step performed by a Doppler disambiguation and phase compensation process (e.g., 180), is to estimate a phase change between Chirp 1 and Chirp 4, or the PRI, denoted as ⁇ (1110).
  • A is unknown, but a measurement of A can be obtained from the detected Doppler cell.
  • This measurement is the estimated phase change, ⁇ , which can be directly obtained using the radial velocity of the Doppler detection cell V ⁇ r by the following:
  • a next step executed by Radar MCPU 150 is to establish the set of transmitter phase compensation hypotheses (1120).
  • the following process is used to establish the hypotheses.
  • CIT is a constant across all chirps
  • i 1, 2, 3:
  • hypotheses are fixed with respect to each Doppler cell, so once a hypothesis is established for the first time, that hypothesis can be stored and reused until the TDM transmitter number or scheduled sequence is changed. In addition, the correct phase compensation cannot be found unless a correct hypothesis is also found. Therefore, a next step of the phase compensation solution process is identifying the correct hypothesis to obtain a corresponding angle response by testing each hypothesis (1140).
  • the correct hypothesis can be identified based on the spurious level of its angle spectrum, which is defined as a number of spectral points above a predefined threshold.
  • the correct hypothesis should lead to the least spurious angle spectrum (i.e. the spectrum that has the fewest points above the threshold, as compared to the other spectra).
  • C m numel Y m > TH
  • is the magnitude of the angle spectrum of an m-th hypothesis
  • TH is the threshold
  • numel ( ⁇ ) is an operation that counts a number of elements of the test vector ⁇ being true.
  • the threshold, TH is set between a minimum target and the demonstrated noise (1130). That is, the threshold is set lower than the lowest peak in the spectrum and higher than the noise floor. The determination of the threshold is performed prior to identifying the correct hypothesis (1140).
  • Another advantage of embodiments of the present invention is that beside being applicable to a conventional uniform linear array (ULA), the rule is applicable to a sparse array as well (i.e., a ULA with few holes).
  • a higher sidelobe level produced by a sparse array can adversely affect detection of the correct hypothesis, which requires the fewest spectral points above threshold.
  • the threshold, TH should be elevated according to the increased sparsity, since the C m of correct hypothesis, which correspond to the ideal MIMO sparse array that has more uniform sidelobe level, will drop much faster than the wrong hypotheses.
  • the fewest spectral points spectrum will translate to the correct hypothesis when an appropriate threshold is selected.
  • Figures 6A , 6B , 7A , 7B , 8A , and 8B are spectral diagrams illustrating examples of hypothesis tests for different levels of ambiguity in A ( Figures 6A , 6B : 0 ⁇ ; Figures 7A , 7B : 2 ⁇ ; Figures 8A , 8B : 4 ⁇ ).
  • Plots 610 Figure 6A
  • 710 Figure 7A
  • 810 Figure 8A
  • Plots 620 Figure 6B
  • 720 Figure 7B
  • 820 Figure 8B
  • Figure 8B illustrate results for each ambiguity level for three targets.
  • the right-hand plot illustrates the phase of the MIMO vector of an ideal MIMO array, the TDM array with error, and the phase of the compensated TDM array using the three hypotheses.
  • the left-hand plot illustrates resulting angle spectrums after applying the hypotheses and the ideal and uncompensated TDM spectrums.
  • a selected threshold, TH is illustrated by a horizontal dotted line.
  • a correct hypothesis is identified as that with a fewest number of peaks above the threshold.
  • Embodiments function regardless of the number of targets present in the range-Doppler cell, as long as the targets share the same Doppler ambiguity. If the ambiguity level differs between the targets, then the algorithm can fail because of an assumption in solving for a common ambiguity. For scenarios in which there is a single target, a correct hypothesis typically leads to a spectrum with a strongest peak and a lowest sidelobe level. This is due to the coherent integration effect, that is, correct compensation leads to the highest possible coherent integration.
  • the peak level test does not apply to scenarios with multiple targets even when the Doppler ambiguity is the same.
  • the three-target H1 spectrum of 620 has the highest spectral peak, but that is not the correct hypothesis.
  • the correct hypothesis, H0 does not result in the highest spectral peak but has the least spurious spectrum.
  • the three-target H2 spectrum of 720 has the highest spectral peak in that figure, but it is not the correct hypothesis (H1 is the correct, least spurious, hypothesis).
  • the three-target H0 spectrum of 820 has the highest spectral peak, but that is not the correct hypothesis (H2 is the correct hypothesis).
  • a sparse array (e.g., a ULA with few holes) is also compatible with embodiments of the hypothesis tests but a higher threshold level is used.
  • a correct hypothesis H1, H2 and H3 is selected as desired .
  • the plot 910 ( Figure 9A ) is the result from a one-target scenario
  • plot 920 ( Figure 9B ) is a three-target scenario.
  • the method functions for a single target case with a sparse array. But an additional confidence level test should be performed in multiple-target case to secure the high-test integrity. The confidence level test will be discussed in greater detail below in conjunction with a non-common ambiguity scenario, which similarly needs the confidence level test.
  • the proposed method can be extrapolated to TDM MIMO radar systems having two transmitters or more than three transmitters.
  • N TX hypotheses are established and tested using the least-spurious spectrum criteria discussed above for correct application of phase compensation.
  • a 1,1 A 1,2 A 1,3 ⁇ A 1 , N A m , 1 A m , 2 A m , 3 ⁇ A m , N A N , 1 A N , 2 A N , 3 ⁇ A N , N 1 ⁇ 1 ⁇ 1 N th 0 ⁇ A ⁇ N ⁇ 2 A ⁇ N ⁇ ⁇ ⁇ N ⁇ 1 A ⁇ N ⁇ 2 ⁇ N 0 0 0 ⁇ 0 m ⁇ 1 ⁇ 1 m ⁇ 1 ⁇ 2 ⁇ m ⁇ 1 ⁇ N ⁇ 1 0 N ⁇ 1 ⁇ 1 N ⁇ 1 ⁇ 2
  • x i,j is MIMO virtual array element output corresponding to TX i and RX j .
  • x ⁇ i,j,m is the compensated output under the hypothesis H(m - 1).
  • An angle spectrum corresponding to the hypothesis H(m - 1) can be found as the Fourier Transform of the array spatial measurement vector consisting of elements of [ x ⁇ i,j,m ].
  • Figures 10A , 10B and 10C depict an example of a two-target case in which the plot 1010 is a scenario in which the A ambiguity are identical.
  • a threshold crossing count no longer can reliably indicate a hypothesis with a lowest count value.
  • the plots 1020 and 1030 either two similar lower counts between the hypotheses are obtained or all three counts are similar, so a correct hypothesis cannot be identified with high confidence.
  • the following sanity check should be performed (see, e.g., Figure 11 element 1150).
  • the hypothesis selection should be flagged as LOW CONFIDENCE if any of the following conditions are met. Otherwise it should be flagged as HIGH CONFIDENCE.
  • phase compensation associated with that identified hypothesis is applied during Doppler disambiguation and phase compensation processing 180 to derive a compensated array vector 182 that is used for angle estimation processing 185 and target tracking 190.
  • Embodiments of the present invention provide a capability for resolving Doppler ambiguity within a single frame that is applicable to an arbitrary number of TDM transmitters used in a MIMO Radar.
  • Embodiments are tolerant to a multiple target condition that does not lead to strongest peaks leading to the correct phase compensation. Further, in scenarios in which the Doppler ambiguity of multiple targets are different, embodiments can flag the results as low confidence, thereby reducing risks associated with such situations.
  • embodiments have a tolerance to a non-uniform linear array, but a degraded performance may be expected.
  • the ability to resolve Doppler ambiguity within a single frame and to correctly apply phase compensation to the TDM MIMO array of an arbitrary number of transmitters and with a multiple number of targets is superior to previously used methods.
  • the method includes estimating a phase change over a pulse repetition interval (PRI) of data from a range-Doppler cell measured by the TDM MIMO radar, determining a set of transmitter phase compensation hypotheses using the estimated phase change, identifying a correct hypothesis from the set of transmitter phase hypotheses, and applying a phase compensation associated with the identified hypothesis to a MIMO array element.
  • PRI pulse repetition interval
  • estimating the phase change over the PRI includes using a measured radial velocity of a target in a Doppler detection cell to calculate a measured phase change.
  • determining the set of transmitter phase compensation hypotheses includes determining a phase change corresponding to a start of each chirp interval time in a PRI.
  • determining the set of transmitter phase compensation hypotheses further includes adjusting the phase changes corresponding to the start of each chirp interval time by modulo 2 ⁇ to acquire an actual phase change measurement for each hypothesis.
  • identifying the correct hypothesis of the set of hypotheses further includes applying each hypothesis to obtain an associated corrected angle response spectrum from the range-Doppler cell data, and associating the correct hypothesis with a corrected angle response spectrum that includes the fewest spectral points above a threshold.
  • determining the threshold includes setting the threshold above a peak noise level for the angle response spectrum, and setting the threshold below a lowest peak in the angle response spectrum.
  • the method further includes determining a confidence level of the identified correct hypothesis.
  • determining the confidence level includes setting the confidence level as low confidence when one or more the following criteria is satisfied: an absolute difference between a lowest count of peaks above the threshold in a first spectrum and a second lowest count of peaks above the threshold in a second spectrum is not greater than a predetermined difference, a ratio of the second lowest count and the lowest count is not lower than a second threshold, and the lowest count is above a third threshold.
  • determining the confidence level comprises: setting the confidence level as low confidence when one or more of the following criteria is satisfied: an absolute difference between a lowest count of peaks above the threshold in a first spectrum and a second lowest count of peaks above the threshold in a second spectrum is not greater than a predetermined difference, a ratio of the second lowest count and the lowest count is not lower than a second threshold, and the lowest count is above a third threshold.
  • a TDM MIMO radar system in another embodiment, includes a linear frequency modulation TD-MIMO radar device and a radar microcontroller and processing unit coupled to an output of the LFM TD-MIMO radar device.
  • the LFM TD-MIMO radar device includes a first plurality of RF transmitter units and a second plurality of RF receiver units.
  • the radar microcontroller and processing unit is configured to receive digital domain signals from the second plurality of receiver units, convert the digital domain signals to an uncompensated array vector including information associated with one or more detected range Doppler cells, estimate a phase change over a pulse repetition interval of data from a range-Doppler cell of the one or more detected range-Doppler cells, determine a set of transmitter phase compensation hypotheses using the estimated phase change, identify a correct hypothesis from the set of transmitter phase hypotheses, and apply a phase compensation associated with the identified hypothesis to a MIMO array element.
  • the radar microcontroller and processing unit is configured to estimate the phase change over the PRI of data by being further configured to use a measured radial velocity of a target in a Doppler detection cell to calculate a measured phase change.
  • the radar microcontroller and processing unit is configured to determine the set of transmitter phase compensation hypotheses by being further configured to determine a phase change corresponding to a start of each chirp interval time in a PRI.
  • the radar microcontroller and processing unit is configured to determine the set of transmitter phase compensation hypotheses by being further configured to adjust the phase changes corresponding to the start of each chirp interval time by modulo 2 ⁇ to acquire an actual phase change measurement for each hypothesis.
  • the radar microcontroller and processing unit is configured to identify the correct hypothesis of the set of hypotheses by being further configured to apply each hypothesis to obtain an associated corrected angle response spectrum from the range-Doppler cell data, and associate the correct hypothesis with a corrected angle response spectrum that includes a fewest spectral points above a threshold.
  • the radar microcontroller and processing unit is configured to determine the threshold by being further configured to set the threshold above a peak noise level for the angle response spectrum, and set the threshold below a lowest peak in the angle response spectrum.
  • the radar microcontroller and processing unit is further configured to determine a confidence level of the identified correct hypothesis.
  • the radar microcontroller and processing unit is configured to determine the confidence level by being further configured to set the confidence level as low confidence when one or more of the following criteria are satisfied: an absolute difference between a lowest count of peaks above the threshold in a first spectrum and a second lowest count of peaks above the threshold in a second spectrum is not greater than a predetermined difference, a ratio of the second lowest count and the lowest count is not lower than a second threshold, and the lowest count is above a third threshold.
  • the radar microcontroller and processing unit is configured to determine the confidence level by being further configured to: set the confidence level as low confidence when one or more of the following criteria is satisfied: an absolute difference between a lowest count of peaks above the threshold in a first spectrum and a second lowest count of peaks above the threshold in a second spectrum is not greater than a predetermined difference, a ratio of the second lowest count and the lowest count is not lower than a second threshold, and the lowest count is above a third threshold.
  • Another embodiment provides a processor coupled to a radar device including a first plurality of RF transmitter units and a second plurality of RF receiver units.
  • the processor is configured to execute a set of instructions configured for estimating a phase change over a pulse repetition interval of data from a range-Doppler cell measured by the radar device, determining a set of transmitter phase compensation hypotheses using the estimated phase change, identifying a correct hypothesis from the set of transmitter phase hypotheses, and applying a phase compensation associated with the identified hypothesis to a MIMO array element.
  • the instructions configured for estimating the phase change over the PRI of data further include instructions configured for using a measured radial velocity of a target in a Doppler detection cell to calculate a measured phase change.
  • the instructions configured for determining the set of transmitter phase compensation hypotheses further include instructions configured for determining a phase change corresponding to a start of each chirp interval time in a PRI.
  • the instructions configured for identifying the correct hypothesis of the set of hypotheses include instructions configured for applying each hypothesis to obtain and associated corrected angle response spectrum from the range-Doppler cell data, and associating the correct hypothesis with a corrected angle response spectrum that includes a fewest spectral points above a threshold.
  • program is defined as a sequence of instructions designed for execution on a computer system.
  • a program, or computer program may include a subroutine, a function, a procedure, an object method, an object implementation, an executable application, an applet, a servlet, a source code, an object code, a shared library/dynamic load library and/or other sequence of instructions designed for execution on a computer system.
  • any two components herein combined to achieve a particular functionality can be seen as “associated with” each other such that the desired functionality is achieved, irrespective of architectures or intermedial components.
  • any two components so associated can also be viewed as being “operably connected,” or “operably coupled,” to each other to achieve the desired functionality.
  • radar system 100 are circuitry located on a single integrated circuit or within a same device.
  • radar system 100 may include any number of separate integrated circuits or separate devices interconnected with each other.
  • radar device 110 and radar MCPU 150 may be located on separate integrated circuits or devices.
  • All or some of the program elements described herein may be received elements of radar system 100, for example, from computer readable media.
  • Such computer readable media may be permanently, removably or remotely coupled to an information processing system such as system 10.
  • the computer readable media may include, for example and without limitation, any number of the following: magnetic storage media including disk and tape storage media; optical storage media such as compact disk media (e.g., CD-ROM, CD-R, etc.) and digital video disk storage media; nonvolatile memory storage media including semiconductor-based memory units such as FLASH memory, EEPROM, EPROM, ROM; ferromagnetic digital memories; MRAM; volatile storage media including registers, buffers or caches, main memory, RAM, etc.; and data transmission media including computer networks, point-to-point telecommunication equipment, and carrier wave transmission media, just to name a few.
  • Coupled is not intended to be limited to a direct coupling or a mechanical coupling.

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EP22157351.2A 2021-02-27 2022-02-17 Verfahren und system zur zeitmultiplex mimo radardoppler-kompensation unter verwendung von hypothesentests mit störwinkelspektrum Pending EP4050365A1 (de)

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